A portfolio of many of the projects I've worked on during high school. Most are in Java, a few are in Python.
Unfortunately, I cannot include any of the code I've written for my jobs due to non-disclosure issues. However, I will summarize them below.
CLARESE is a specialized model built on the TensorFlow object-detection API. Its purpose is to review inspection videos for risers, subsea pipelines that carry various fluids between oil rigs and drilling stations, and annotate anomalies and fractures that it sees. By doing so, CLARESE seeks to reduce the number of man-hours required to inspect footage of risers. I have spent over 300 hours on CLARESE, easily making it the largest project I've ever worked on. CLARESE is also the first exposure I've had to artificial intelligence and machine learning. I went in completely blind, and ended up forming a product with real-world applications and a meaningful success rate. The learning curve was immensely steep, but the journey was amazing nonetheless. At the same time I was building CLARESE, I was working my first office job and started to grasp ideas of how professional development works.
PATTERN is a trained spaCy model designed to extract design information regarding various subsea components, such as Riser Joints and Wellheads. By extracting this information automatically, PATTERN seeks to reduce the number of man-hours required to pull this information for proper organization and storage. Pattern is a newer project, with just about 75 hours of work put into it.